IR c7-c8

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Questions and Answers

Why is accuracy not practical for evaluating search results?

It can show 100% accuracy with zero results. (correct)

It does not consider document relevance.

It is difficult to measure in real-time.

It requires extensive computational resources.

What happens to recall and precision when more documents are included in search results?

Both recall and precision increase.

Neither recall nor precision is affected.

Recall increases while precision decreases. (correct)

Precision increases while recall decreases.

What is meant by interpolated precision?

An average of all precision values over all queries.

A method to rank documents by their original scores.

The highest precision observed at the highest recall rate. (correct)

A calculation method for average precision across multiple searches.

Why is it important to look at statistical variance in search systems?

To measure the response consistency of a system to different queries. Signup and view all the answers

What role does anchor text play in search engine quality signaling?

It links a specific term to different pages across the web. Signup and view all the answers

What is a primary reason for evaluating search systems?

To ensure they function as intended Signup and view all the answers

Which method is NOT effective for measuring user satisfaction?

Conducting a survey about user preferences Signup and view all the answers

What is the correct definition of precision in information retrieval?

The ratio of relevant documents retrieved to total documents retrieved Signup and view all the answers

How is recall defined in the context of information retrieval?

The fraction of relevant documents that are found Signup and view all the answers

What is the primary purpose of relevance assessments in information retrieval?

To determine whether a document answers the search query Signup and view all the answers

What does the F-measure represent in information retrieval?

A harmonic mean of precision and recall Signup and view all the answers

Which benchmark measurement is specifically used to assess agreement among two or more evaluators?

Cohen’s kappa Signup and view all the answers

In which scenario is recall particularly important?

When searching for patents Signup and view all the answers

What does citation frequency refer to?

The frequency of a document being cited Signup and view all the answers

Which method is used to calculate PageRank?

Analyzing the quality of incoming links Signup and view all the answers

What do shared references indicate?

Articles that link to the same article Signup and view all the answers

Which characteristic describes a strongly connected Markov chain?

Every point is reachable from every other point Signup and view all the answers

What is meant by the term 'sink' in the context of PageRank?

A page with no incoming links Signup and view all the answers

What is the role of teleport in a Markov chain?

To connect specific points with random jumps Signup and view all the answers

Which of the following best defines a stationary solution in Markov chains?

A solution that stabilizes after a number of steps Signup and view all the answers

What is the significance of using an adjacency matrix in link analysis?

To visualize the flow of links among pages Signup and view all the answers

Study Notes

College 7 & 18-11

Why Evaluation?
- To ensure the system is functioning as intended.
- User satisfaction is a subjective measure.
- Allows comparison of systems.

Measuring User Satisfaction

Web Search Engine: Observe if users find what they are looking for.
Web Shop: Observe if users find, select, and purchase items.
Controlled Experiments: Task-based user testing.
User-Generated Queries: Testing users' own queries.

Information Retrieval

Information Needs: Understanding why users seek specific information.
Relevant Documents: Documents that properly respond to the user query.

Determining Document Relevance

Relevance Benchmark Measurement:
- Requires a benchmark document collection and a benchmark set of information needs expressed as queries.
- A relevance assessment for each query-document pair.
Standard Relevance Benchmark:
- Human experts determine relevance of each document.
- Measuring rater agreement involves two or more evaluators. Cohen's Kappa is used to evaluate agreement.

Precision and Recall

Precision: The fraction of retrieved documents that are relevant. (TP / (TP + FP))
Recall: The fraction of relevant documents that are retrieved. (TP / (TP + FN))

When is Precision/Recall Important?

Web search: Precision is more important.
Corporate database: Both precision and recall are important.
Patent search: Recall is usually more crucial.

F-Measure

Harmonic mean of precision and recall.
Weighs precision and recall equally (F1).

Accuracy

The fraction of correctly classified documents. (TP + TN) / (TP + TN + FP + FN)
Not a good measure for information retrieval.

Evaluation of Ranked Results

Systems can have various numbers of results.
Evaluating precision and recall at varying levels.
Increasing number of retrieved documents causes recall to increase and precision to decrease.

Precision-Recall Curve

Shows the trade-off between precision and recall at various levels of recall.
Interpolated precision: The highest precision at a given level of recall.
Average precision: The average of precision at each level of recall.
- 11-point interpolated average precision is a standard measure in TREC competitions.

Mean Average Precision (MAP)

Average of precisions interpolated at different levels of recall.
A good measure because it includes precision evaluation at multiple levels of recall and averages them.

Avoiding Interpolation

Map(Q): (Summation(Precision(Rjk) / number of relevant documents per query)).

Statistical Variation

Systems respond differently to various queries.
Variance analysis is used to assess variability in system performance across different queries for a comparison of systems.

College 8 (21-11-2024)

When Term-Ranking Breaks

Distinguishing similar terms such as different pages and document types with high frequency of a keyword (eg, multiple descriptions on an IBM page versus an informational spam page)
IBM's copyright page (high frequency) vs. spam page (high frequency) vs. IBM homepage (term in image/other elements)

Links and Anchors

Hyperlinks between documents as a quality signal.
Anchor text as input for similarity matching

Citation Frequency

The frequency of a document being cited.

Co-Citation

Documents or papers linked together.

Shared References

Articles that cite/link to same articles.

Link Analysis Measures

PageRank (Google): Estimate an important of a page.
HITS (Hyperlink-Induced Topic Search)
TrustRank (Yahoo): A link analysis based measure.

PageRank

Estimating the importance of a page on the web, considering incoming links.

The Web as a Graph

Represents web pages as nodes and hyperlinks as edges.

Full PageRank: Example and Calculation

Demonstrates calculation of PageRank using iterative calculations.
The final PageRank value is used to generate a score to be used on webpages.

Random Surfer model

Probability of being on a page based on teleport and random links.

Markov Chains

PageRank calculations can be formulated as a Markov chain.
Adjacency matrices are critical to this calculation because they determine the probabilities of proceeding from one page to another.

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Description

This quiz covers the essential concepts of evaluating systems and measuring user satisfaction in the context of information retrieval. It includes topics like user needs, document relevance, and the methods of benchmarking relevance. Understand how user interactions with web platforms help in assessing their effectiveness.